Giannopoulou Eugenia, Elemento Olivier
Biological Sciences Department, New York City College of Technology, City University of New York, New York, NY, USA.
Arthritis and Tissue Degeneration Program and the David Z. Rosensweig Genomics Research Center, Hospital for Special Surgery, New York, NY, USA.
Methods Mol Biol. 2017;1507:43-58. doi: 10.1007/978-1-4939-6518-2_4.
Chromatin immunoprecipitation followed by sequencing is an invaluable assay for identifying the genomic binding sites of transcription factors. However, transcription factors rarely bind chromatin alone but often bind together with other cofactors, forming protein complexes. Here, we describe a computational method that integrates multiple ChIP-seq and RNA-seq datasets to discover protein complexes and determine their role as activators or repressors. This chapter outlines a detailed computational pipeline for discovering and predicting binding partners from ChIP-seq data and inferring their role in regulating gene expression. This work aims at developing hypotheses about gene regulation via binding partners and deciphering the combinatorial nature of DNA-binding proteins.
染色质免疫沉淀测序是鉴定转录因子基因组结合位点的一项重要检测方法。然而,转录因子很少单独结合染色质,而是常常与其他辅因子一起结合,形成蛋白质复合物。在此,我们描述了一种计算方法,该方法整合多个染色质免疫沉淀测序(ChIP-seq)和RNA测序(RNA-seq)数据集,以发现蛋白质复合物并确定它们作为激活因子或抑制因子的作用。本章概述了一个详细的计算流程,用于从ChIP-seq数据中发现和预测结合伙伴,并推断它们在调节基因表达中的作用。这项工作旨在通过结合伙伴提出有关基因调控的假设,并解读DNA结合蛋白的组合性质。